Overview

Brought to you by YData

Dataset statistics

Number of variables34
Number of observations100090
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory26.0 MiB
Average record size in memory272.0 B

Variable types

Text7
DateTime1
Categorical1
Numeric25

Alerts

breadth is highly overall correlated with depthHigh correlation
depth is highly overall correlated with breadthHigh correlation
Rating is highly imbalanced (61.7%) Imbalance
Helpfulness is highly skewed (γ1 = 37.68498276) Skewed
Helpfulness has 91665 (91.6%) zeros Zeros

Reproduction

Analysis started2025-01-22 07:03:31.061979
Analysis finished2025-01-22 07:06:14.975908
Duration2 minutes and 43.91 seconds
Software versionydata-profiling vv4.12.1
Download configurationconfig.json

Variables

Distinct100087
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:15.505915image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9827
Median length3044
Mean length247.30879
Min length9

Characters and Unicode

Total characters24753137
Distinct characters67
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100084 ?
Unique (%)> 99.9%

Sample

1st rowI enjoyed both The Martian and Artemis so I preordered this one and started it immediately It did not disappoint Andy Weir is one of my favorite authors and Ray Porter is one of my favorite narrators so this combination is a winwin The narration is superb and the writing is great I recommend this book Dont over think it This is worth the price of admissionDisclaimer My enjoyment of the narrator is based on my listening speed I only leave 5 stars for books Ive listened to or will listen to multiple times
2nd rowAwesome story telling Great build up of the characters and universe Cant compare to The Martian as that was novelunique, but this absolutely crushes Artemis Reminds me of a cross between Old Mans War and the Three Body Problem but slightly less cerebral than the latter
3rd rowLet me start off by saying that I strongly enjoyed The Martian and Artemis please, please dont let the negative comments of others dissuade you from reading Artemis Until yesterday, American Gods was my unrivaled favorite as of finishing Project Hail Mary, it is now tied for my very favorite I will not provide spoilers, but if you enjoy good science fiction Scalzi, Taylor, Adams and understand that what makes good science fiction is good science, get Project Hail MaryAs for Ray Porter, I fell in love with his narration of We Are Legion We Are Bob and its sequels His enthusiastic, geeky, humorous, witty, and sarcastic tones are an absolute delight to my ears No other narrator could have done as well or betterI dont regret preordering both the audiobook and a signed copy of Project Hail Mary in the slightest To the contrary, I am elated and am looking forward to listening to this audiobook many, many times
4th rowEvery once in a while Ill finish a book and cant help but get a bit depressed Knowing that the magic and intrigue you felt can never quite be captured again Part of this comes from completing it so quickly, I just couldnt put it down The other was I KNEW I would love it just because it was written by Andy Weir Most books it takes a few chapters to start getting into it but was hooked from the startWithout giving anything away Id say that its a mix of the Bobiverse and the Martian The amazing adventure that comes with space while geeking out on science projects
5th rowIn the Martian his high school science lecture content was acceptable because of the suspense Here, which as far as I can tell is an attempt to recreate that, it totally fails After several hours of boring basic science and NOTHING at all happening, I had enough Its just dull, the attempt at suspense seems manufactured and theres no action I really liked Artemis, and wish hes written a sequel to that I am returning this one disappointed
ValueCountFrequency (%)
the 233344
 
5.2%
and 155291
 
3.4%
i 141305
 
3.1%
to 132311
 
2.9%
a 117343
 
2.6%
of 100599
 
2.2%
this 90405
 
2.0%
it 85428
 
1.9%
is 68450
 
1.5%
book 66648
 
1.5%
Other values (70694) 3336194
73.7%
2025-01-22T16:06:16.334941image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4497685
18.2%
e 2314234
 
9.3%
t 1856343
 
7.5%
o 1623132
 
6.6%
a 1559287
 
6.3%
i 1414888
 
5.7%
n 1334949
 
5.4%
s 1230181
 
5.0%
r 1180807
 
4.8%
h 985183
 
4.0%
Other values (57) 6756448
27.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 24753137
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
4497685
18.2%
e 2314234
 
9.3%
t 1856343
 
7.5%
o 1623132
 
6.6%
a 1559287
 
6.3%
i 1414888
 
5.7%
n 1334949
 
5.4%
s 1230181
 
5.0%
r 1180807
 
4.8%
h 985183
 
4.0%
Other values (57) 6756448
27.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 24753137
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
4497685
18.2%
e 2314234
 
9.3%
t 1856343
 
7.5%
o 1623132
 
6.6%
a 1559287
 
6.3%
i 1414888
 
5.7%
n 1334949
 
5.4%
s 1230181
 
5.0%
r 1180807
 
4.8%
h 985183
 
4.0%
Other values (57) 6756448
27.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 24753137
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
4497685
18.2%
e 2314234
 
9.3%
t 1856343
 
7.5%
o 1623132
 
6.6%
a 1559287
 
6.3%
i 1414888
 
5.7%
n 1334949
 
5.4%
s 1230181
 
5.0%
r 1180807
 
4.8%
h 985183
 
4.0%
Other values (57) 6756448
27.3%
Distinct5319
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size782.1 KiB
Minimum2002-12-19 00:00:00
Maximum2024-12-04 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-01-22T16:06:16.561053image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:06:16.825514image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Rating
Categorical

Imbalance 

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size782.1 KiB
5
83790 
4
10110 
3
 
3038
1
 
1633
2
 
1519

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters100090
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row5
3rd row5
4th row5
5th row4

Common Values

ValueCountFrequency (%)
5 83790
83.7%
4 10110
 
10.1%
3 3038
 
3.0%
1 1633
 
1.6%
2 1519
 
1.5%

Length

2025-01-22T16:06:17.071509image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-01-22T16:06:17.278328image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
5 83790
83.7%
4 10110
 
10.1%
3 3038
 
3.0%
1 1633
 
1.6%
2 1519
 
1.5%

Most occurring characters

ValueCountFrequency (%)
5 83790
83.7%
4 10110
 
10.1%
3 3038
 
3.0%
1 1633
 
1.6%
2 1519
 
1.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 100090
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
5 83790
83.7%
4 10110
 
10.1%
3 3038
 
3.0%
1 1633
 
1.6%
2 1519
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 100090
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
5 83790
83.7%
4 10110
 
10.1%
3 3038
 
3.0%
1 1633
 
1.6%
2 1519
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 100090
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
5 83790
83.7%
4 10110
 
10.1%
3 3038
 
3.0%
1 1633
 
1.6%
2 1519
 
1.5%

Average_Rating
Real number (ℝ)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.649985
Minimum4
Maximum4.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:17.490607image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile4.3
Q14.6
median4.7
Q34.8
95-th percentile4.9
Maximum4.9
Range0.9
Interquartile range (IQR)0.2

Descriptive statistics

Standard deviation0.1888161
Coefficient of variation (CV)0.040605744
Kurtosis0.56831933
Mean4.649985
Median Absolute Deviation (MAD)0.1
Skewness-0.81639395
Sum465417
Variance0.03565152
MonotonicityNot monotonic
2025-01-22T16:06:17.679607image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
4.6 22809
22.8%
4.7 20961
20.9%
4.8 18423
18.4%
4.9 14772
14.8%
4.4 8096
 
8.1%
4.5 7369
 
7.4%
4.3 4603
 
4.6%
4.2 1408
 
1.4%
4 846
 
0.8%
4.1 803
 
0.8%
ValueCountFrequency (%)
4 846
 
0.8%
4.1 803
 
0.8%
4.2 1408
 
1.4%
4.3 4603
 
4.6%
4.4 8096
 
8.1%
4.5 7369
 
7.4%
4.6 22809
22.8%
4.7 20961
20.9%
4.8 18423
18.4%
4.9 14772
14.8%
ValueCountFrequency (%)
4.9 14772
14.8%
4.8 18423
18.4%
4.7 20961
20.9%
4.6 22809
22.8%
4.5 7369
 
7.4%
4.4 8096
 
8.1%
4.3 4603
 
4.6%
4.2 1408
 
1.4%
4.1 803
 
0.8%
4 846
 
0.8%

Num_of_Ratings
Real number (ℝ)

Distinct100
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44889.823
Minimum98
Maximum215239
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:17.946968image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum98
5-th percentile5126
Q113701
median26734
Q352781
95-th percentile182379
Maximum215239
Range215141
Interquartile range (IQR)39080

Descriptive statistics

Standard deviation50348.856
Coefficient of variation (CV)1.1216096
Kurtosis3.9449164
Mean44889.823
Median Absolute Deviation (MAD)15281
Skewness2.1661403
Sum4.4930224 × 109
Variance2.5350073 × 109
MonotonicityNot monotonic
2025-01-22T16:06:18.197804image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
182379 1803
 
1.8%
54757 1739
 
1.7%
36116 1723
 
1.7%
52781 1678
 
1.7%
15885 1653
 
1.7%
45875 1648
 
1.6%
181868 1646
 
1.6%
32619 1630
 
1.6%
101379 1629
 
1.6%
36876 1627
 
1.6%
Other values (90) 83314
83.2%
ValueCountFrequency (%)
98 23
 
< 0.1%
101 26
 
< 0.1%
138 43
< 0.1%
180 33
 
< 0.1%
243 77
0.1%
463 58
0.1%
561 68
0.1%
1031 75
0.1%
1033 100
0.1%
1042 89
0.1%
ValueCountFrequency (%)
215239 1575
1.6%
202151 1600
1.6%
196712 1578
1.6%
182379 1803
1.8%
181868 1646
1.6%
104740 1538
1.5%
101379 1629
1.6%
89067 1582
1.6%
79190 1381
1.4%
62022 1598
1.6%

Helpfulness
Real number (ℝ)

Skewed  Zeros 

Distinct178
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.60107903
Minimum0
Maximum656
Zeros91665
Zeros (%)91.6%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:18.444370image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum656
Range656
Interquartile range (IQR)0

Descriptive statistics

Standard deviation8.5868327
Coefficient of variation (CV)14.285697
Kurtosis1960.1281
Mean0.60107903
Median Absolute Deviation (MAD)0
Skewness37.684983
Sum60162
Variance73.733696
MonotonicityNot monotonic
2025-01-22T16:06:18.697190image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 91665
91.6%
1 4964
 
5.0%
2 1182
 
1.2%
3 550
 
0.5%
4 314
 
0.3%
5 161
 
0.2%
6 124
 
0.1%
7 96
 
0.1%
8 84
 
0.1%
9 60
 
0.1%
Other values (168) 890
 
0.9%
ValueCountFrequency (%)
0 91665
91.6%
1 4964
 
5.0%
2 1182
 
1.2%
3 550
 
0.5%
4 314
 
0.3%
5 161
 
0.2%
6 124
 
0.1%
7 96
 
0.1%
8 84
 
0.1%
9 60
 
0.1%
ValueCountFrequency (%)
656 1
< 0.1%
640 1
< 0.1%
597 1
< 0.1%
596 1
< 0.1%
467 1
< 0.1%
456 1
< 0.1%
452 1
< 0.1%
445 1
< 0.1%
438 1
< 0.1%
429 1
< 0.1%
Distinct63245
Distinct (%)63.2%
Missing0
Missing (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:19.619236image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length758
Median length142
Mean length10.107993
Min length1

Characters and Unicode

Total characters1011709
Distinct characters267
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55705 ?
Unique (%)55.7%

Sample

1st rowDavidgonzalezsr
2nd rowDavid
3rd rowRoswatheist
4th rowJ. Kenney
5th rowCelia
ValueCountFrequency (%)
customer 6471
 
3.9%
amazon 5285
 
3.2%
anonymous 3914
 
2.3%
user 3865
 
2.3%
m 1588
 
1.0%
a 1378
 
0.8%
j 1324
 
0.8%
s 1197
 
0.7%
kindle 1196
 
0.7%
c 1136
 
0.7%
Other values (41911) 139759
83.6%
2025-01-22T16:06:20.972498image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 90784
 
9.0%
a 85561
 
8.5%
n 71118
 
7.0%
67155
 
6.6%
r 62900
 
6.2%
o 59364
 
5.9%
i 54228
 
5.4%
s 46081
 
4.6%
l 41373
 
4.1%
t 35585
 
3.5%
Other values (257) 397560
39.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1011709
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 90784
 
9.0%
a 85561
 
8.5%
n 71118
 
7.0%
67155
 
6.6%
r 62900
 
6.2%
o 59364
 
5.9%
i 54228
 
5.4%
s 46081
 
4.6%
l 41373
 
4.1%
t 35585
 
3.5%
Other values (257) 397560
39.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1011709
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 90784
 
9.0%
a 85561
 
8.5%
n 71118
 
7.0%
67155
 
6.6%
r 62900
 
6.2%
o 59364
 
5.9%
i 54228
 
5.4%
s 46081
 
4.6%
l 41373
 
4.1%
t 35585
 
3.5%
Other values (257) 397560
39.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1011709
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 90784
 
9.0%
a 85561
 
8.5%
n 71118
 
7.0%
67155
 
6.6%
r 62900
 
6.2%
o 59364
 
5.9%
i 54228
 
5.4%
s 46081
 
4.6%
l 41373
 
4.1%
t 35585
 
3.5%
Other values (257) 397560
39.3%
Distinct63153
Distinct (%)63.1%
Missing0
Missing (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:21.688578image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length128
Median length115
Mean length21.540603
Min length1

Characters and Unicode

Total characters2155999
Distinct characters64
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57934 ?
Unique (%)57.9%

Sample

1st rowBazinga
2nd rowAbsolutely Great way better than Artemis
3rd rowHighest Order of Geekgasm Medal
4th rowSo good, its depressing
5th rowNOT the Martian
ValueCountFrequency (%)
a 12243
 
3.3%
the 10523
 
2.9%
book 9450
 
2.6%
story 9427
 
2.6%
and 9103
 
2.5%
great 8956
 
2.4%
of 6214
 
1.7%
it 5913
 
1.6%
this 5607
 
1.5%
to 5511
 
1.5%
Other values (13802) 285690
77.5%
2025-01-22T16:06:23.223876image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
272693
 
12.6%
e 200659
 
9.3%
t 158261
 
7.3%
o 147440
 
6.8%
a 135604
 
6.3%
i 130735
 
6.1%
n 129283
 
6.0%
r 120945
 
5.6%
s 91733
 
4.3%
l 84558
 
3.9%
Other values (54) 684088
31.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2155999
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
272693
 
12.6%
e 200659
 
9.3%
t 158261
 
7.3%
o 147440
 
6.8%
a 135604
 
6.3%
i 130735
 
6.1%
n 129283
 
6.0%
r 120945
 
5.6%
s 91733
 
4.3%
l 84558
 
3.9%
Other values (54) 684088
31.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2155999
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
272693
 
12.6%
e 200659
 
9.3%
t 158261
 
7.3%
o 147440
 
6.8%
a 135604
 
6.3%
i 130735
 
6.1%
n 129283
 
6.0%
r 120945
 
5.6%
s 91733
 
4.3%
l 84558
 
3.9%
Other values (54) 684088
31.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2155999
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
272693
 
12.6%
e 200659
 
9.3%
t 158261
 
7.3%
o 147440
 
6.8%
a 135604
 
6.3%
i 130735
 
6.1%
n 129283
 
6.0%
r 120945
 
5.6%
s 91733
 
4.3%
l 84558
 
3.9%
Other values (54) 684088
31.7%

Link
Text

Distinct100
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:24.167828image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length104
Median length80
Mean length65.561704
Min length50

Characters and Unicode

Total characters6562071
Distinct characters65
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowhttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K
2nd rowhttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K
3rd rowhttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K
4th rowhttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K
5th rowhttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K
ValueCountFrequency (%)
https://www.audible.com/pd/project-hail-mary-audiobook/b08g9prs1k 1803
 
1.8%
https://www.audible.com/pd/circe-audiobook/b0794bxzbf 1739
 
1.7%
https://www.audible.com/pd/the-handmaids-tale-special-edition-audiobook/b06xfw9yz5 1723
 
1.7%
https://www.audible.com/pd/the-sandman-audiobook/b086wp794z 1678
 
1.7%
https://www.audible.com/pd/the-mystwick-school-of-musicraft-audiobook/b07mt4mtgp 1653
 
1.7%
https://www.audible.com/pd/the-hate-u-give-audiobook/b01nagd7tv 1648
 
1.6%
https://www.audible.com/pd/becoming-audiobook/b07b3bcz9s 1646
 
1.6%
https://www.audible.com/pd/evil-eye-audiobook/b07qp1x8b7 1630
 
1.6%
https://www.audible.com/pd/the-nightingale-audiobook/b00nybqkfq 1629
 
1.6%
https://www.audible.com/pd/kitchen-confidential-audiobook/b002va8gsa 1627
 
1.6%
Other values (90) 83314
83.2%
2025-01-22T16:06:25.531357image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 500450
 
7.6%
o 491236
 
7.5%
d 349712
 
5.3%
- 326860
 
5.0%
i 312280
 
4.8%
w 309080
 
4.7%
e 296420
 
4.5%
t 285896
 
4.4%
u 227886
 
3.5%
b 214375
 
3.3%
Other values (55) 3247876
49.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6562071
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 500450
 
7.6%
o 491236
 
7.5%
d 349712
 
5.3%
- 326860
 
5.0%
i 312280
 
4.8%
w 309080
 
4.7%
e 296420
 
4.5%
t 285896
 
4.4%
u 227886
 
3.5%
b 214375
 
3.3%
Other values (55) 3247876
49.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6562071
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 500450
 
7.6%
o 491236
 
7.5%
d 349712
 
5.3%
- 326860
 
5.0%
i 312280
 
4.8%
w 309080
 
4.7%
e 296420
 
4.5%
t 285896
 
4.4%
u 227886
 
3.5%
b 214375
 
3.3%
Other values (55) 3247876
49.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6562071
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 500450
 
7.6%
o 491236
 
7.5%
d 349712
 
5.3%
- 326860
 
5.0%
i 312280
 
4.8%
w 309080
 
4.7%
e 296420
 
4.5%
t 285896
 
4.4%
u 227886
 
3.5%
b 214375
 
3.3%
Other values (55) 3247876
49.5%
Distinct100
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:26.279887image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length27
Median length25
Mean length22.381287
Min length10

Characters and Unicode

Total characters2240143
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row162833,15895,2619,672,360
2nd row162833,15895,2619,672,360
3rd row162833,15895,2619,672,360
4th row162833,15895,2619,672,360
5th row162833,15895,2619,672,360
ValueCountFrequency (%)
162833,15895,2619,672,360 1803
 
1.8%
42989,8803,2159,494,312 1739
 
1.7%
24398,7248,2683,1000,787 1723
 
1.7%
41741,6347,2482,1077,1134 1678
 
1.7%
12241,2785,628,123,108 1653
 
1.7%
38215,5922,1240,276,222 1648
 
1.6%
167358,11293,2099,526,592 1646
 
1.6%
21973,7120,2395,652,479 1630
 
1.6%
88056,10560,1913,488,362 1629
 
1.6%
30168,5163,1181,203,161 1627
 
1.6%
Other values (90) 83314
83.2%
2025-01-22T16:06:27.289039image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 400360
17.9%
1 293283
13.1%
2 235603
10.5%
3 197365
8.8%
4 194297
8.7%
6 180444
8.1%
5 159101
 
7.1%
8 158986
 
7.1%
9 143216
 
6.4%
7 140322
 
6.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2240143
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
, 400360
17.9%
1 293283
13.1%
2 235603
10.5%
3 197365
8.8%
4 194297
8.7%
6 180444
8.1%
5 159101
 
7.1%
8 158986
 
7.1%
9 143216
 
6.4%
7 140322
 
6.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2240143
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
, 400360
17.9%
1 293283
13.1%
2 235603
10.5%
3 197365
8.8%
4 194297
8.7%
6 180444
8.1%
5 159101
 
7.1%
8 158986
 
7.1%
9 143216
 
6.4%
7 140322
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2240143
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
, 400360
17.9%
1 293283
13.1%
2 235603
10.5%
3 197365
8.8%
4 194297
8.7%
6 180444
8.1%
5 159101
 
7.1%
8 158986
 
7.1%
9 143216
 
6.4%
7 140322
 
6.3%
Distinct100
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:27.878178image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length25
Median length23
Mean length21.234129
Min length10

Characters and Unicode

Total characters2125324
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row156733,7989,1298,287,227
2nd row156733,7989,1298,287,227
3rd row156733,7989,1298,287,227
4th row156733,7989,1298,287,227
5th row156733,7989,1298,287,227
ValueCountFrequency (%)
156733,7989,1298,287,227 1803
 
1.8%
43762,4431,816,203,134 1739
 
1.7%
24729,5316,1623,518,402 1723
 
1.7%
41992,2633,727,328,483 1678
 
1.7%
12353,1605,321,55,61 1653
 
1.7%
36667,3855,831,145,134 1648
 
1.6%
150764,8445,1619,378,412 1646
 
1.6%
24192,3973,1106,296,275 1630
 
1.6%
79759,9539,1759,409,288 1629
 
1.6%
26805,3001,736,128,75 1627
 
1.6%
Other values (90) 83314
83.2%
2025-01-22T16:06:28.851212image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 400360
18.8%
1 267664
12.6%
2 229020
10.8%
3 185731
8.7%
5 168791
7.9%
6 159705
 
7.5%
4 152021
 
7.2%
7 145325
 
6.8%
8 144417
 
6.8%
0 141208
 
6.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2125324
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
, 400360
18.8%
1 267664
12.6%
2 229020
10.8%
3 185731
8.7%
5 168791
7.9%
6 159705
 
7.5%
4 152021
 
7.2%
7 145325
 
6.8%
8 144417
 
6.8%
0 141208
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2125324
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
, 400360
18.8%
1 267664
12.6%
2 229020
10.8%
3 185731
8.7%
5 168791
7.9%
6 159705
 
7.5%
4 152021
 
7.2%
7 145325
 
6.8%
8 144417
 
6.8%
0 141208
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2125324
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
, 400360
18.8%
1 267664
12.6%
2 229020
10.8%
3 185731
8.7%
5 168791
7.9%
6 159705
 
7.5%
4 152021
 
7.2%
7 145325
 
6.8%
8 144417
 
6.8%
0 141208
 
6.6%
Distinct100
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:29.510995image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length26
Median length24
Mean length22.147257
Min length10

Characters and Unicode

Total characters2216719
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row145112,16872,2818,763,416
2nd row145112,16872,2818,763,416
3rd row145112,16872,2818,763,416
4th row145112,16872,2818,763,416
5th row145112,16872,2818,763,416
ValueCountFrequency (%)
145112,16872,2818,763,416 1803
 
1.8%
37805,8286,2189,532,302 1739
 
1.7%
21863,6313,2504,957,853 1723
 
1.7%
35483,5976,2420,1029,1076 1678
 
1.7%
10595,2743,765,147,92 1653
 
1.7%
34350,5452,1234,255,189 1648
 
1.6%
146729,11086,1957,499,466 1646
 
1.6%
19324,6598,2562,726,499 1630
 
1.6%
79872,9093,1753,489,325 1629
 
1.6%
25132,4213,975,162,95 1627
 
1.6%
Other values (90) 83314
83.2%
2025-01-22T16:06:30.562906image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 400360
18.1%
1 294153
13.3%
2 245146
11.1%
3 193262
8.7%
5 190961
8.6%
6 166979
7.5%
4 165851
7.5%
7 157768
 
7.1%
8 146072
 
6.6%
9 128681
 
5.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2216719
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
, 400360
18.1%
1 294153
13.3%
2 245146
11.1%
3 193262
8.7%
5 190961
8.6%
6 166979
7.5%
4 165851
7.5%
7 157768
 
7.1%
8 146072
 
6.6%
9 128681
 
5.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2216719
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
, 400360
18.1%
1 294153
13.3%
2 245146
11.1%
3 193262
8.7%
5 190961
8.6%
6 166979
7.5%
4 165851
7.5%
7 157768
 
7.1%
8 146072
 
6.6%
9 128681
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2216719
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
, 400360
18.1%
1 294153
13.3%
2 245146
11.1%
3 193262
8.7%
5 190961
8.6%
6 166979
7.5%
4 165851
7.5%
7 157768
 
7.1%
8 146072
 
6.6%
9 128681
 
5.8%

depth
Real number (ℝ)

High correlation 

Distinct99982
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.67560614
Minimum1.6186847 × 10-17
Maximum1.30103
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:30.913702image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1.6186847 × 10-17
5-th percentile0.35739299
Q10.55937339
median0.68405526
Q30.80370503
95-th percentile0.9616401
Maximum1.30103
Range1.30103
Interquartile range (IQR)0.24433164

Descriptive statistics

Standard deviation0.18393477
Coefficient of variation (CV)0.27225148
Kurtosis0.25891901
Mean0.67560614
Median Absolute Deviation (MAD)0.12203715
Skewness-0.32743092
Sum67621.419
Variance0.033832001
MonotonicityNot monotonic
2025-01-22T16:06:31.292440image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.301029996 68
 
0.1%
2.26133266 × 10-174
 
< 0.1%
5.886437322 × 10-174
 
< 0.1%
0.2924290578 4
 
< 0.1%
0.4087912555 3
 
< 0.1%
0.8278201947 3
 
< 0.1%
2.395013465 × 10-173
 
< 0.1%
0.2165280183 3
 
< 0.1%
1.990172214 × 10-173
 
< 0.1%
0.2387074008 3
 
< 0.1%
Other values (99972) 99992
99.9%
ValueCountFrequency (%)
1.61868469 × 10-171
 
< 0.1%
1.990172214 × 10-173
< 0.1%
2.027827986 × 10-171
 
< 0.1%
2.114208353 × 10-172
< 0.1%
2.141186158 × 10-171
 
< 0.1%
2.146494167 × 10-171
 
< 0.1%
2.199991856 × 10-171
 
< 0.1%
2.26133266 × 10-174
< 0.1%
2.29617743 × 10-171
 
< 0.1%
2.328608107 × 10-171
 
< 0.1%
ValueCountFrequency (%)
1.301029996 68
0.1%
1.213690195 1
 
< 0.1%
1.213380736 1
 
< 0.1%
1.203049455 1
 
< 0.1%
1.199383364 1
 
< 0.1%
1.195252796 1
 
< 0.1%
1.187609869 1
 
< 0.1%
1.186300649 1
 
< 0.1%
1.183184479 1
 
< 0.1%
1.181206845 1
 
< 0.1%

breadth
Real number (ℝ)

High correlation 

Distinct99922
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9646677
Minimum0.099687938
Maximum5.0118159
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:31.834075image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0.099687938
5-th percentile0.94893435
Q11.4810867
median1.9241914
Q32.3905454
95-th percentile3.1379008
Maximum5.0118159
Range4.912128
Interquartile range (IQR)0.90945873

Descriptive statistics

Standard deviation0.67087299
Coefficient of variation (CV)0.34146893
Kurtosis0.22459815
Mean1.9646677
Median Absolute Deviation (MAD)0.45437648
Skewness0.42943521
Sum196643.59
Variance0.45007057
MonotonicityNot monotonic
2025-01-22T16:06:32.170224image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.09968793816 68
 
0.1%
3.111655457 21
 
< 0.1%
3.84107568 21
 
< 0.1%
3.316064522 8
 
< 0.1%
4.447450954 6
 
< 0.1%
4.431445186 6
 
< 0.1%
4.370041585 5
 
< 0.1%
4.891800849 4
 
< 0.1%
3.498971163 4
 
< 0.1%
4.573091861 3
 
< 0.1%
Other values (99912) 99944
99.9%
ValueCountFrequency (%)
0.09968793816 68
0.1%
0.1805746767 1
 
< 0.1%
0.2033294144 1
 
< 0.1%
0.2438388208 1
 
< 0.1%
0.2458035522 1
 
< 0.1%
0.2554012804 1
 
< 0.1%
0.28397665 1
 
< 0.1%
0.2874190988 1
 
< 0.1%
0.2940187832 1
 
< 0.1%
0.2942412325 1
 
< 0.1%
ValueCountFrequency (%)
5.011815889 2
< 0.1%
4.999085009 1
 
< 0.1%
4.902848857 1
 
< 0.1%
4.899428659 1
 
< 0.1%
4.891800849 4
< 0.1%
4.889150534 1
 
< 0.1%
4.871047734 2
< 0.1%
4.864083668 1
 
< 0.1%
4.862658891 3
< 0.1%
4.847517887 1
 
< 0.1%

Topic_1
Real number (ℝ)

Distinct99980
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.045833586
Minimum2.8401182 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:32.628521image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2.8401182 × 10-20
5-th percentile6.3463486 × 10-20
Q17.7737267 × 10-5
median0.011055749
Q30.07042916
95-th percentile0.16655344
Maximum1
Range1
Interquartile range (IQR)0.070351423

Descriptive statistics

Standard deviation0.070809652
Coefficient of variation (CV)1.5449293
Kurtosis23.336305
Mean0.045833586
Median Absolute Deviation (MAD)0.011055749
Skewness3.5660923
Sum4587.4837
Variance0.0050140068
MonotonicityNot monotonic
2025-01-22T16:06:33.223708image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.05 68
 
0.1%
1 6
 
< 0.1%
6.196289274 × 10-204
 
< 0.1%
4.708774073 × 10-204
 
< 0.1%
0.238758031 3
 
< 0.1%
6.571319854 × 10-203
 
< 0.1%
5.437215329 × 10-203
 
< 0.1%
0.1986851101 3
 
< 0.1%
4.610600655 × 10-193
 
< 0.1%
0.09501978876 3
 
< 0.1%
Other values (99970) 99990
99.9%
ValueCountFrequency (%)
2.840118182 × 10-201
< 0.1%
2.840253967 × 10-201
< 0.1%
2.852876755 × 10-201
< 0.1%
2.953432943 × 10-201
< 0.1%
2.965494723 × 10-201
< 0.1%
2.971759128 × 10-201
< 0.1%
2.979744931 × 10-201
< 0.1%
2.985114267 × 10-201
< 0.1%
2.996278886 × 10-201
< 0.1%
2.996669913 × 10-201
< 0.1%
ValueCountFrequency (%)
1 6
< 0.1%
0.9971889546 1
 
< 0.1%
0.9962289384 1
 
< 0.1%
0.9873065958 1
 
< 0.1%
0.9631837382 1
 
< 0.1%
0.9515954574 1
 
< 0.1%
0.9473151497 1
 
< 0.1%
0.9436295914 1
 
< 0.1%
0.942276308 1
 
< 0.1%
0.9293300302 1
 
< 0.1%

Topic_2
Real number (ℝ)

Distinct99978
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.10040726
Minimum2.6811042 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:34.655525image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2.6811042 × 10-20
5-th percentile6.4245255 × 10-20
Q11.7950833 × 10-19
median0.028471109
Q30.16501217
95-th percentile0.37822674
Maximum1
Range1
Interquartile range (IQR)0.16501217

Descriptive statistics

Standard deviation0.139921
Coefficient of variation (CV)1.3935347
Kurtosis4.7519042
Mean0.10040726
Median Absolute Deviation (MAD)0.028471109
Skewness1.9577752
Sum10049.762
Variance0.019577886
MonotonicityNot monotonic
2025-01-22T16:06:35.009119image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.05 68
 
0.1%
1 8
 
< 0.1%
1.649460308 × 10-194
 
< 0.1%
4.708774073 × 10-204
 
< 0.1%
6.971312359 × 10-203
 
< 0.1%
6.571319854 × 10-203
 
< 0.1%
5.437215329 × 10-203
 
< 0.1%
4.177598406 × 10-203
 
< 0.1%
0.07698649075 3
 
< 0.1%
6.096213638 × 10-203
 
< 0.1%
Other values (99968) 99988
99.9%
ValueCountFrequency (%)
2.681104154 × 10-201
< 0.1%
2.784495699 × 10-201
< 0.1%
2.842027472 × 10-201
< 0.1%
2.953432943 × 10-201
< 0.1%
2.960301288 × 10-201
< 0.1%
2.965494723 × 10-201
< 0.1%
2.971807717 × 10-201
< 0.1%
2.979744931 × 10-201
< 0.1%
2.985114267 × 10-201
< 0.1%
3.008641624 × 10-201
< 0.1%
ValueCountFrequency (%)
1 8
< 0.1%
0.9980863696 1
 
< 0.1%
0.99728096 1
 
< 0.1%
0.9956473682 1
 
< 0.1%
0.9956460692 1
 
< 0.1%
0.9944990319 1
 
< 0.1%
0.9932715204 1
 
< 0.1%
0.993170004 1
 
< 0.1%
0.990838122 1
 
< 0.1%
0.9899555496 1
 
< 0.1%

Topic_3
Real number (ℝ)

Distinct99982
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.045943447
Minimum2.7844957 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:36.018117image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2.7844957 × 10-20
5-th percentile5.7970001 × 10-20
Q19.7248977 × 10-20
median0.00053286775
Q30.012703822
95-th percentile0.29692345
Maximum1
Range1
Interquartile range (IQR)0.012703822

Descriptive statistics

Standard deviation0.10895719
Coefficient of variation (CV)2.3715502
Kurtosis9.8642308
Mean0.045943447
Median Absolute Deviation (MAD)0.00053286775
Skewness2.9892927
Sum4598.4796
Variance0.01187167
MonotonicityNot monotonic
2025-01-22T16:06:36.350099image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.05 68
 
0.1%
6.196289274 × 10-204
 
< 0.1%
1.649460308 × 10-194
 
< 0.1%
4.708774073 × 10-204
 
< 0.1%
4.177598406 × 10-203
 
< 0.1%
4.610600655 × 10-193
 
< 0.1%
6.571319854 × 10-203
 
< 0.1%
0.8013148899 3
 
< 0.1%
5.437215329 × 10-203
 
< 0.1%
6.971312359 × 10-203
 
< 0.1%
Other values (99972) 99992
99.9%
ValueCountFrequency (%)
2.784495699 × 10-201
< 0.1%
2.831186365 × 10-201
< 0.1%
2.840253967 × 10-201
< 0.1%
2.842027472 × 10-201
< 0.1%
2.852876755 × 10-201
< 0.1%
2.971759128 × 10-201
< 0.1%
2.971807717 × 10-201
< 0.1%
2.979744931 × 10-201
< 0.1%
2.996278886 × 10-201
< 0.1%
2.996669913 × 10-201
< 0.1%
ValueCountFrequency (%)
1 1
< 0.1%
0.9768043797 1
< 0.1%
0.9689302553 1
< 0.1%
0.9640563025 1
< 0.1%
0.9418198289 1
< 0.1%
0.9399408465 1
< 0.1%
0.937978183 1
< 0.1%
0.9238159441 1
< 0.1%
0.918219195 1
< 0.1%
0.9020990084 1
< 0.1%

Topic_4
Real number (ℝ)

Distinct99982
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.048061543
Minimum2.6811042 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:36.603911image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2.6811042 × 10-20
5-th percentile5.7756931 × 10-20
Q19.6639341 × 10-20
median0.00018896348
Q30.012805681
95-th percentile0.33129968
Maximum1
Range1
Interquartile range (IQR)0.012805681

Descriptive statistics

Standard deviation0.12150786
Coefficient of variation (CV)2.5281723
Kurtosis11.225687
Mean0.048061543
Median Absolute Deviation (MAD)0.00018896348
Skewness3.2141524
Sum4810.4798
Variance0.014764161
MonotonicityNot monotonic
2025-01-22T16:06:36.860458image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.05 68
 
0.1%
6.196289274 × 10-204
 
< 0.1%
1.649460308 × 10-194
 
< 0.1%
4.708774073 × 10-204
 
< 0.1%
4.177598406 × 10-203
 
< 0.1%
4.610600655 × 10-193
 
< 0.1%
6.571319854 × 10-203
 
< 0.1%
6.096213638 × 10-203
 
< 0.1%
5.437215329 × 10-203
 
< 0.1%
6.971312359 × 10-203
 
< 0.1%
Other values (99972) 99992
99.9%
ValueCountFrequency (%)
2.681104154 × 10-201
< 0.1%
2.784495699 × 10-201
< 0.1%
2.840118182 × 10-201
< 0.1%
2.852876755 × 10-201
< 0.1%
2.960301288 × 10-201
< 0.1%
2.971759128 × 10-201
< 0.1%
2.971807717 × 10-201
< 0.1%
2.996278886 × 10-201
< 0.1%
2.996669913 × 10-201
< 0.1%
3.053411503 × 10-201
< 0.1%
ValueCountFrequency (%)
1 2
< 0.1%
0.9941689346 1
< 0.1%
0.9922496035 1
< 0.1%
0.9895538165 1
< 0.1%
0.9865482235 1
< 0.1%
0.9850039458 1
< 0.1%
0.9829713554 1
< 0.1%
0.9817647857 1
< 0.1%
0.9804921737 1
< 0.1%
0.9794669729 1
< 0.1%

Topic_5
Real number (ℝ)

Distinct99982
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.050175044
Minimum2.8311864 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:37.117356image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2.8311864 × 10-20
5-th percentile5.7746375 × 10-20
Q11.0418843 × 10-19
median0.0025489029
Q30.024909345
95-th percentile0.28130098
Maximum1
Range1
Interquartile range (IQR)0.024909345

Descriptive statistics

Standard deviation0.10756428
Coefficient of variation (CV)2.1437805
Kurtosis11.338901
Mean0.050175044
Median Absolute Deviation (MAD)0.0025489029
Skewness3.0428373
Sum5022.0202
Variance0.011570074
MonotonicityNot monotonic
2025-01-22T16:06:37.381940image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.05 68
 
0.1%
6.196289274 × 10-204
 
< 0.1%
1.649460308 × 10-194
 
< 0.1%
0.4008201031 4
 
< 0.1%
4.177598406 × 10-203
 
< 0.1%
0.05262974149 3
 
< 0.1%
6.571319854 × 10-203
 
< 0.1%
6.096213638 × 10-203
 
< 0.1%
5.437215329 × 10-203
 
< 0.1%
0.761241969 3
 
< 0.1%
Other values (99972) 99992
99.9%
ValueCountFrequency (%)
2.831186365 × 10-201
< 0.1%
2.840253967 × 10-201
< 0.1%
2.852876755 × 10-201
< 0.1%
2.878903144 × 10-201
< 0.1%
2.953432943 × 10-201
< 0.1%
2.965494723 × 10-201
< 0.1%
2.971759128 × 10-201
< 0.1%
2.990896896 × 10-201
< 0.1%
2.996278886 × 10-201
< 0.1%
3.002504146 × 10-201
< 0.1%
ValueCountFrequency (%)
1 1
< 0.1%
0.9990260718 1
< 0.1%
0.9987211027 1
< 0.1%
0.9939443231 1
< 0.1%
0.9830449373 1
< 0.1%
0.9825841317 1
< 0.1%
0.9692629692 1
< 0.1%
0.9633859284 1
< 0.1%
0.961808416 1
< 0.1%
0.9588883301 1
< 0.1%

Topic_6
Real number (ℝ)

Distinct99980
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.042010917
Minimum2.7844957 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:37.651471image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2.7844957 × 10-20
5-th percentile5.6468544 × 10-20
Q19.4547956 × 10-20
median0.00094358744
Q30.01516215
95-th percentile0.2965377
Maximum1
Range1
Interquartile range (IQR)0.01516215

Descriptive statistics

Standard deviation0.11087541
Coefficient of variation (CV)2.6392048
Kurtosis14.601517
Mean0.042010917
Median Absolute Deviation (MAD)0.00094358744
Skewness3.6082956
Sum4204.8727
Variance0.012293358
MonotonicityNot monotonic
2025-01-22T16:06:37.900318image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.05 68
 
0.1%
6.196289274 × 10-204
 
< 0.1%
0.5991798969 4
 
< 0.1%
1.649460308 × 10-194
 
< 0.1%
6.096213638 × 10-203
 
< 0.1%
6.971312359 × 10-203
 
< 0.1%
5.437215329 × 10-203
 
< 0.1%
0.4544261523 3
 
< 0.1%
6.571319854 × 10-203
 
< 0.1%
4.610600655 × 10-193
 
< 0.1%
Other values (99970) 99992
99.9%
ValueCountFrequency (%)
2.784495699 × 10-201
< 0.1%
2.831186365 × 10-201
< 0.1%
2.840253967 × 10-201
< 0.1%
2.842027472 × 10-201
< 0.1%
2.960301288 × 10-201
< 0.1%
2.965494723 × 10-201
< 0.1%
2.971759128 × 10-201
< 0.1%
2.979744931 × 10-201
< 0.1%
2.985114267 × 10-201
< 0.1%
2.990896896 × 10-201
< 0.1%
ValueCountFrequency (%)
1 3
< 0.1%
0.9995321768 1
 
< 0.1%
0.9917951355 1
 
< 0.1%
0.9905933161 1
 
< 0.1%
0.9879950958 1
 
< 0.1%
0.9752360024 1
 
< 0.1%
0.971656322 1
 
< 0.1%
0.9692976458 1
 
< 0.1%
0.9692791397 1
 
< 0.1%
0.9680276281 1
 
< 0.1%

Topic_7
Real number (ℝ)

Distinct99981
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.034371129
Minimum2.6811042 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:38.151907image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2.6811042 × 10-20
5-th percentile5.6111199 × 10-20
Q18.7824923 × 10-20
median1.7798876 × 10-19
Q30.0078766222
95-th percentile0.27368455
Maximum1
Range1
Interquartile range (IQR)0.0078766222

Descriptive statistics

Standard deviation0.10246784
Coefficient of variation (CV)2.9812184
Kurtosis16.505701
Mean0.034371129
Median Absolute Deviation (MAD)1.2199466 × 10-19
Skewness3.8761068
Sum3440.2063
Variance0.010499659
MonotonicityNot monotonic
2025-01-22T16:06:38.410104image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.05 68
 
0.1%
6.196289274 × 10-204
 
< 0.1%
1.649460308 × 10-194
 
< 0.1%
4.708774073 × 10-204
 
< 0.1%
5.437215329 × 10-203
 
< 0.1%
6.571319854 × 10-203
 
< 0.1%
0.04948251161 3
 
< 0.1%
6.971312359 × 10-203
 
< 0.1%
1 3
 
< 0.1%
4.177598406 × 10-203
 
< 0.1%
Other values (99971) 99992
99.9%
ValueCountFrequency (%)
2.681104154 × 10-201
< 0.1%
2.784495699 × 10-201
< 0.1%
2.878903144 × 10-201
< 0.1%
2.953432943 × 10-201
< 0.1%
2.960301288 × 10-201
< 0.1%
2.965494723 × 10-201
< 0.1%
2.971807717 × 10-201
< 0.1%
2.979744931 × 10-201
< 0.1%
2.990896896 × 10-201
< 0.1%
3.002504146 × 10-201
< 0.1%
ValueCountFrequency (%)
1 3
< 0.1%
0.9986757388 1
 
< 0.1%
0.9782802524 1
 
< 0.1%
0.9702890885 1
 
< 0.1%
0.9597192774 1
 
< 0.1%
0.9520338145 1
 
< 0.1%
0.9435516467 1
 
< 0.1%
0.937915049 1
 
< 0.1%
0.9351458242 1
 
< 0.1%
0.9327543079 1
 
< 0.1%

Topic_8
Real number (ℝ)

Distinct99981
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.039373744
Minimum2.6811042 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:38.674427image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2.6811042 × 10-20
5-th percentile5.6309826 × 10-20
Q19.4063779 × 10-20
median2.6328794 × 10-19
Q30.029397366
95-th percentile0.21796378
Maximum1
Range1
Interquartile range (IQR)0.029397366

Descriptive statistics

Standard deviation0.092018597
Coefficient of variation (CV)2.3370548
Kurtosis21.180498
Mean0.039373744
Median Absolute Deviation (MAD)2.1431057 × 10-19
Skewness3.996055
Sum3940.918
Variance0.0084674222
MonotonicityNot monotonic
2025-01-22T16:06:39.070506image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.05 68
 
0.1%
1.649460308 × 10-194
 
< 0.1%
6.196289274 × 10-204
 
< 0.1%
4.708774073 × 10-204
 
< 0.1%
6.571319854 × 10-203
 
< 0.1%
4.610600655 × 10-193
 
< 0.1%
6.971312359 × 10-203
 
< 0.1%
4.177598406 × 10-203
 
< 0.1%
5.437215329 × 10-203
 
< 0.1%
6.096213638 × 10-203
 
< 0.1%
Other values (99971) 99992
99.9%
ValueCountFrequency (%)
2.681104154 × 10-201
< 0.1%
2.784495699 × 10-201
< 0.1%
2.831186365 × 10-201
< 0.1%
2.840118182 × 10-201
< 0.1%
2.840253967 × 10-201
< 0.1%
2.842027472 × 10-201
< 0.1%
2.852876755 × 10-201
< 0.1%
2.953432943 × 10-201
< 0.1%
2.960301288 × 10-201
< 0.1%
2.965494723 × 10-201
< 0.1%
ValueCountFrequency (%)
1 2
< 0.1%
0.9981719155 1
< 0.1%
0.9979921817 1
< 0.1%
0.9959707874 1
< 0.1%
0.9957604401 1
< 0.1%
0.9944264359 1
< 0.1%
0.9934139801 1
< 0.1%
0.990704894 1
< 0.1%
0.9900683332 1
< 0.1%
0.9897811613 1
< 0.1%

Topic_9
Real number (ℝ)

Distinct99982
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.030995102
Minimum2.7844957 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:39.469853image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2.7844957 × 10-20
5-th percentile5.6216542 × 10-20
Q19.3940188 × 10-20
median9.4166542 × 10-19
Q30.0097104587
95-th percentile0.22801748
Maximum1
Range1
Interquartile range (IQR)0.0097104587

Descriptive statistics

Standard deviation0.090522571
Coefficient of variation (CV)2.9205444
Kurtosis21.215641
Mean0.030995102
Median Absolute Deviation (MAD)9.0735297 × 10-19
Skewness4.217361
Sum3102.2997
Variance0.0081943359
MonotonicityNot monotonic
2025-01-22T16:06:39.943571image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.05 68
 
0.1%
6.196289274 × 10-204
 
< 0.1%
1.649460308 × 10-194
 
< 0.1%
4.708774073 × 10-204
 
< 0.1%
4.177598406 × 10-203
 
< 0.1%
0.0360534795 3
 
< 0.1%
6.571319854 × 10-203
 
< 0.1%
6.096213638 × 10-203
 
< 0.1%
5.437215329 × 10-203
 
< 0.1%
6.971312359 × 10-203
 
< 0.1%
Other values (99972) 99992
99.9%
ValueCountFrequency (%)
2.784495699 × 10-201
< 0.1%
2.831186365 × 10-201
< 0.1%
2.840253967 × 10-201
< 0.1%
2.852876755 × 10-201
< 0.1%
2.878903144 × 10-201
< 0.1%
2.953432943 × 10-201
< 0.1%
2.971759128 × 10-201
< 0.1%
2.971807717 × 10-201
< 0.1%
2.979744931 × 10-201
< 0.1%
2.985114267 × 10-201
< 0.1%
ValueCountFrequency (%)
1 2
< 0.1%
0.998927938 1
< 0.1%
0.9876387187 1
< 0.1%
0.9804980899 1
< 0.1%
0.9773829147 1
< 0.1%
0.9749142907 1
< 0.1%
0.9724393684 1
< 0.1%
0.9718260223 1
< 0.1%
0.9687211143 1
< 0.1%
0.9661178938 1
< 0.1%

Topic_10
Real number (ℝ)

Distinct99981
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.046027913
Minimum2.6811042 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:40.199453image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2.6811042 × 10-20
5-th percentile5.6599402 × 10-20
Q19.3010326 × 10-20
median2.9521115 × 10-19
Q30.018458457
95-th percentile0.29012197
Maximum1
Range1
Interquartile range (IQR)0.018458457

Descriptive statistics

Standard deviation0.10917108
Coefficient of variation (CV)2.371845
Kurtosis12.362486
Mean0.046027913
Median Absolute Deviation (MAD)2.4843846 × 10-19
Skewness3.2609689
Sum4606.9338
Variance0.011918324
MonotonicityNot monotonic
2025-01-22T16:06:40.471178image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.05 68
 
0.1%
4.708774073 × 10-204
 
< 0.1%
6.196289274 × 10-204
 
< 0.1%
1.649460308 × 10-194
 
< 0.1%
5.437215329 × 10-203
 
< 0.1%
4.177598406 × 10-203
 
< 0.1%
0.05498829535 3
 
< 0.1%
6.571319854 × 10-203
 
< 0.1%
6.096213638 × 10-203
 
< 0.1%
6.971312359 × 10-203
 
< 0.1%
Other values (99971) 99992
99.9%
ValueCountFrequency (%)
2.681104154 × 10-201
< 0.1%
2.831186365 × 10-201
< 0.1%
2.840118182 × 10-201
< 0.1%
2.840253967 × 10-201
< 0.1%
2.842027472 × 10-201
< 0.1%
2.852876755 × 10-201
< 0.1%
2.878903144 × 10-201
< 0.1%
2.953432943 × 10-201
< 0.1%
2.960301288 × 10-201
< 0.1%
2.965494723 × 10-201
< 0.1%
ValueCountFrequency (%)
1 2
< 0.1%
0.9916418621 1
< 0.1%
0.9878106278 1
< 0.1%
0.9871483014 1
< 0.1%
0.9821158403 1
< 0.1%
0.9812301315 1
< 0.1%
0.9771457686 1
< 0.1%
0.9740456236 1
< 0.1%
0.9739221303 1
< 0.1%
0.9662003417 1
< 0.1%

Topic_11
Real number (ℝ)

Distinct99978
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.04836001
Minimum2.6811042 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:40.739258image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2.6811042 × 10-20
5-th percentile5.6888804 × 10-20
Q19.6065458 × 10-20
median0.00068532044
Q30.026997555
95-th percentile0.30338999
Maximum1
Range1
Interquartile range (IQR)0.026997555

Descriptive statistics

Standard deviation0.11261141
Coefficient of variation (CV)2.3286061
Kurtosis12.565736
Mean0.04836001
Median Absolute Deviation (MAD)0.00068532044
Skewness3.3068509
Sum4840.3534
Variance0.01268133
MonotonicityNot monotonic
2025-01-22T16:06:41.007192image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.05 68
 
0.1%
1 5
 
< 0.1%
4.708774073 × 10-204
 
< 0.1%
6.196289274 × 10-204
 
< 0.1%
1.649460308 × 10-194
 
< 0.1%
5.437215329 × 10-203
 
< 0.1%
0.3690675164 3
 
< 0.1%
6.571319854 × 10-203
 
< 0.1%
6.971312359 × 10-203
 
< 0.1%
0.450554059 3
 
< 0.1%
Other values (99968) 99990
99.9%
ValueCountFrequency (%)
2.681104154 × 10-201
< 0.1%
2.784495699 × 10-201
< 0.1%
2.831186365 × 10-201
< 0.1%
2.840118182 × 10-201
< 0.1%
2.840253967 × 10-201
< 0.1%
2.842027472 × 10-201
< 0.1%
2.878903144 × 10-201
< 0.1%
2.953432943 × 10-201
< 0.1%
2.960301288 × 10-201
< 0.1%
2.979744931 × 10-201
< 0.1%
ValueCountFrequency (%)
1 5
< 0.1%
0.999163425 1
 
< 0.1%
0.995803288 1
 
< 0.1%
0.9942683766 1
 
< 0.1%
0.9937218775 1
 
< 0.1%
0.9930624503 1
 
< 0.1%
0.9909040951 1
 
< 0.1%
0.9840281788 1
 
< 0.1%
0.9761855223 1
 
< 0.1%
0.9724233159 1
 
< 0.1%

Topic_12
Real number (ℝ)

Distinct99981
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.033683809
Minimum2.6811042 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:41.267332image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2.6811042 × 10-20
5-th percentile5.6354271 × 10-20
Q18.865441 × 10-20
median1.7201703 × 10-19
Q30.012074546
95-th percentile0.26422628
Maximum1
Range1
Interquartile range (IQR)0.012074546

Descriptive statistics

Standard deviation0.099173031
Coefficient of variation (CV)2.9442345
Kurtosis18.199841
Mean0.033683809
Median Absolute Deviation (MAD)1.1428667 × 10-19
Skewness4.0522563
Sum3371.4124
Variance0.0098352901
MonotonicityNot monotonic
2025-01-22T16:06:41.537404image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.05 68
 
0.1%
1 4
 
< 0.1%
6.196289274 × 10-204
 
< 0.1%
1.649460308 × 10-194
 
< 0.1%
4.708774073 × 10-204
 
< 0.1%
6.571319854 × 10-203
 
< 0.1%
4.610600655 × 10-193
 
< 0.1%
6.971312359 × 10-203
 
< 0.1%
4.177598406 × 10-203
 
< 0.1%
6.096213638 × 10-203
 
< 0.1%
Other values (99971) 99991
99.9%
ValueCountFrequency (%)
2.681104154 × 10-201
< 0.1%
2.842027472 × 10-201
< 0.1%
2.878903144 × 10-201
< 0.1%
2.953432943 × 10-201
< 0.1%
2.965494723 × 10-201
< 0.1%
2.971807717 × 10-201
< 0.1%
2.985114267 × 10-201
< 0.1%
2.990896896 × 10-201
< 0.1%
3.002504146 × 10-201
< 0.1%
3.008641624 × 10-201
< 0.1%
ValueCountFrequency (%)
1 4
< 0.1%
0.999816306 1
 
< 0.1%
0.9642182841 1
 
< 0.1%
0.9557174539 1
 
< 0.1%
0.9482986292 1
 
< 0.1%
0.9444883998 1
 
< 0.1%
0.9353032126 1
 
< 0.1%
0.9329917389 1
 
< 0.1%
0.9328088694 1
 
< 0.1%
0.9178396409 1
 
< 0.1%

Topic_13
Real number (ℝ)

Distinct99981
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.034171851
Minimum2.6811042 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:41.791941image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2.6811042 × 10-20
5-th percentile5.6740254 × 10-20
Q19.4131193 × 10-20
median3.7370944 × 10-19
Q30.012167342
95-th percentile0.24835408
Maximum1
Range1
Interquartile range (IQR)0.012167342

Descriptive statistics

Standard deviation0.096063783
Coefficient of variation (CV)2.8111964
Kurtosis18.844705
Mean0.034171851
Median Absolute Deviation (MAD)3.2931133 × 10-19
Skewness4.0086825
Sum3420.2606
Variance0.0092282505
MonotonicityNot monotonic
2025-01-22T16:06:42.063765image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.05 68
 
0.1%
1.649460308 × 10-194
 
< 0.1%
6.196289274 × 10-204
 
< 0.1%
4.708774073 × 10-204
 
< 0.1%
6.571319854 × 10-203
 
< 0.1%
6.096213638 × 10-203
 
< 0.1%
5.437215329 × 10-203
 
< 0.1%
6.971312359 × 10-203
 
< 0.1%
0.01221380121 3
 
< 0.1%
4.177598406 × 10-203
 
< 0.1%
Other values (99971) 99992
99.9%
ValueCountFrequency (%)
2.681104154 × 10-201
< 0.1%
2.784495699 × 10-201
< 0.1%
2.840253967 × 10-201
< 0.1%
2.842027472 × 10-201
< 0.1%
2.852876755 × 10-201
< 0.1%
2.878903144 × 10-201
< 0.1%
2.960301288 × 10-201
< 0.1%
2.971759128 × 10-201
< 0.1%
2.971807717 × 10-201
< 0.1%
2.985114267 × 10-201
< 0.1%
ValueCountFrequency (%)
1 2
< 0.1%
0.9971889943 1
< 0.1%
0.9966992805 1
< 0.1%
0.9931252627 1
< 0.1%
0.9915358875 1
< 0.1%
0.9890250199 1
< 0.1%
0.9778308805 1
< 0.1%
0.9723209061 1
< 0.1%
0.9711270746 1
< 0.1%
0.962695864 1
< 0.1%

Topic_14
Real number (ℝ)

Distinct99979
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.046344912
Minimum2.6811042 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:42.321157image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2.6811042 × 10-20
5-th percentile5.6099838 × 10-20
Q19.8696894 × 10-20
median0.0037872738
Q30.03107254
95-th percentile0.27028654
Maximum1
Range1
Interquartile range (IQR)0.03107254

Descriptive statistics

Standard deviation0.10337014
Coefficient of variation (CV)2.2304529
Kurtosis15.179338
Mean0.046344912
Median Absolute Deviation (MAD)0.0037872738
Skewness3.4995829
Sum4638.6622
Variance0.010685386
MonotonicityNot monotonic
2025-01-22T16:06:42.591325image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.05 68
 
0.1%
1 6
 
< 0.1%
4.708774073 × 10-204
 
< 0.1%
1.649460308 × 10-194
 
< 0.1%
6.196289274 × 10-204
 
< 0.1%
6.096213638 × 10-203
 
< 0.1%
4.177598406 × 10-203
 
< 0.1%
5.437215329 × 10-203
 
< 0.1%
6.971312359 × 10-203
 
< 0.1%
4.610600655 × 10-193
 
< 0.1%
Other values (99969) 99989
99.9%
ValueCountFrequency (%)
2.681104154 × 10-201
< 0.1%
2.831186365 × 10-201
< 0.1%
2.840118182 × 10-201
< 0.1%
2.840253967 × 10-201
< 0.1%
2.852876755 × 10-201
< 0.1%
2.878903144 × 10-201
< 0.1%
2.960301288 × 10-201
< 0.1%
2.965494723 × 10-201
< 0.1%
2.971759128 × 10-201
< 0.1%
2.971807717 × 10-201
< 0.1%
ValueCountFrequency (%)
1 6
< 0.1%
0.9984950868 1
 
< 0.1%
0.9984768273 1
 
< 0.1%
0.9943902947 1
 
< 0.1%
0.9901727972 1
 
< 0.1%
0.9882888457 1
 
< 0.1%
0.9845198431 1
 
< 0.1%
0.9772439129 1
 
< 0.1%
0.9748413408 1
 
< 0.1%
0.9675195006 1
 
< 0.1%

Topic_15
Real number (ℝ)

Distinct99962
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.069778397
Minimum2.6811042 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:42.853809image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2.6811042 × 10-20
5-th percentile5.4607079 × 10-20
Q19.633025 × 10-20
median0.01225978
Q30.075335062
95-th percentile0.34510184
Maximum1
Range1
Interquartile range (IQR)0.075335062

Descriptive statistics

Standard deviation0.12968395
Coefficient of variation (CV)1.8585115
Kurtosis11.09025
Mean0.069778397
Median Absolute Deviation (MAD)0.01225978
Skewness3.0056384
Sum6984.1197
Variance0.016817928
MonotonicityNot monotonic
2025-01-22T16:06:43.161456image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.05 68
 
0.1%
1 21
 
< 0.1%
1.649460308 × 10-194
 
< 0.1%
4.708774073 × 10-204
 
< 0.1%
6.196289274 × 10-204
 
< 0.1%
6.096213638 × 10-203
 
< 0.1%
4.610600655 × 10-193
 
< 0.1%
6.571319854 × 10-203
 
< 0.1%
6.971312359 × 10-203
 
< 0.1%
5.437215329 × 10-203
 
< 0.1%
Other values (99952) 99974
99.9%
ValueCountFrequency (%)
2.681104154 × 10-201
< 0.1%
2.784495699 × 10-201
< 0.1%
2.831186365 × 10-201
< 0.1%
2.840118182 × 10-201
< 0.1%
2.840253967 × 10-201
< 0.1%
2.842027472 × 10-201
< 0.1%
2.852876755 × 10-201
< 0.1%
2.878903144 × 10-201
< 0.1%
2.953432943 × 10-201
< 0.1%
2.960301288 × 10-201
< 0.1%
ValueCountFrequency (%)
1 21
< 0.1%
0.9996573704 1
 
< 0.1%
0.9995956071 1
 
< 0.1%
0.9993089066 1
 
< 0.1%
0.9989916196 1
 
< 0.1%
0.9986933598 1
 
< 0.1%
0.9974291363 1
 
< 0.1%
0.9967676868 1
 
< 0.1%
0.9965915424 1
 
< 0.1%
0.9952232266 1
 
< 0.1%

Topic_16
Real number (ℝ)

Distinct99982
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.062181161
Minimum2.7844957 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:43.758164image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2.7844957 × 10-20
5-th percentile5.9070819 × 10-20
Q11.0493563 × 10-19
median0.0046669978
Q30.083130915
95-th percentile0.29197079
Maximum1
Range1
Interquartile range (IQR)0.083130915

Descriptive statistics

Standard deviation0.1082031
Coefficient of variation (CV)1.7401267
Kurtosis8.2755063
Mean0.062181161
Median Absolute Deviation (MAD)0.0046669978
Skewness2.5722098
Sum6223.7124
Variance0.01170791
MonotonicityNot monotonic
2025-01-22T16:06:44.027621image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.05 68
 
0.1%
6.196289274 × 10-204
 
< 0.1%
1.649460308 × 10-194
 
< 0.1%
4.708774073 × 10-204
 
< 0.1%
4.177598406 × 10-203
 
< 0.1%
0.1642248897 3
 
< 0.1%
6.571319854 × 10-203
 
< 0.1%
6.096213638 × 10-203
 
< 0.1%
5.437215329 × 10-203
 
< 0.1%
6.971312359 × 10-203
 
< 0.1%
Other values (99972) 99992
99.9%
ValueCountFrequency (%)
2.784495699 × 10-201
< 0.1%
2.831186365 × 10-201
< 0.1%
2.840118182 × 10-201
< 0.1%
2.840253967 × 10-201
< 0.1%
2.842027472 × 10-201
< 0.1%
2.852876755 × 10-201
< 0.1%
2.878903144 × 10-201
< 0.1%
2.953432943 × 10-201
< 0.1%
2.960301288 × 10-201
< 0.1%
2.971759128 × 10-201
< 0.1%
ValueCountFrequency (%)
1 1
< 0.1%
0.999788576 1
< 0.1%
0.9955687575 1
< 0.1%
0.9763739208 1
< 0.1%
0.959627447 1
< 0.1%
0.9560148158 1
< 0.1%
0.9493283676 1
< 0.1%
0.9492678785 1
< 0.1%
0.9470501229 1
< 0.1%
0.9437348233 1
< 0.1%

Topic_17
Real number (ℝ)

Distinct99982
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.035822742
Minimum2.6811042 × 10-20
Maximum0.99909929
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:44.291953image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2.6811042 × 10-20
5-th percentile5.5819951 × 10-20
Q18.9333699 × 10-20
median2.0539678 × 10-19
Q30.018898591
95-th percentile0.23467186
Maximum0.99909929
Range0.99909929
Interquartile range (IQR)0.018898591

Descriptive statistics

Standard deviation0.090867767
Coefficient of variation (CV)2.5365944
Kurtosis17.838592
Mean0.035822742
Median Absolute Deviation (MAD)1.5325462 × 10-19
Skewness3.831003
Sum3585.4982
Variance0.0082569511
MonotonicityNot monotonic
2025-01-22T16:06:44.632086image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.05 68
 
0.1%
6.196289274 × 10-204
 
< 0.1%
1.649460308 × 10-194
 
< 0.1%
4.708774073 × 10-204
 
< 0.1%
4.177598406 × 10-203
 
< 0.1%
0.1504931312 3
 
< 0.1%
6.571319854 × 10-203
 
< 0.1%
6.096213638 × 10-203
 
< 0.1%
5.437215329 × 10-203
 
< 0.1%
6.971312359 × 10-203
 
< 0.1%
Other values (99972) 99992
99.9%
ValueCountFrequency (%)
2.681104154 × 10-201
< 0.1%
2.784495699 × 10-201
< 0.1%
2.831186365 × 10-201
< 0.1%
2.840118182 × 10-201
< 0.1%
2.840253967 × 10-201
< 0.1%
2.842027472 × 10-201
< 0.1%
2.878903144 × 10-201
< 0.1%
2.965494723 × 10-201
< 0.1%
2.971807717 × 10-201
< 0.1%
2.996278886 × 10-201
< 0.1%
ValueCountFrequency (%)
0.9990992854 1
< 0.1%
0.9936570887 1
< 0.1%
0.9917946026 1
< 0.1%
0.9750845039 1
< 0.1%
0.9693089298 1
< 0.1%
0.9621279171 1
< 0.1%
0.9394861193 1
< 0.1%
0.9315428682 1
< 0.1%
0.9285497628 1
< 0.1%
0.9257759693 1
< 0.1%

Topic_18
Real number (ℝ)

Distinct99981
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.037339917
Minimum2.6811042 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:44.921192image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2.6811042 × 10-20
5-th percentile5.4806714 × 10-20
Q19.0350732 × 10-20
median0.0012573948
Q30.01936518
95-th percentile0.2534951
Maximum1
Range1
Interquartile range (IQR)0.01936518

Descriptive statistics

Standard deviation0.10284552
Coefficient of variation (CV)2.7543049
Kurtosis20.591971
Mean0.037339917
Median Absolute Deviation (MAD)0.0012573948
Skewness4.2403572
Sum3737.3523
Variance0.010577201
MonotonicityNot monotonic
2025-01-22T16:06:45.214638image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.05 68
 
0.1%
1.649460308 × 10-194
 
< 0.1%
6.196289274 × 10-204
 
< 0.1%
4.708774073 × 10-204
 
< 0.1%
5.437215329 × 10-203
 
< 0.1%
6.096213638 × 10-203
 
< 0.1%
4.177598406 × 10-203
 
< 0.1%
6.971312359 × 10-203
 
< 0.1%
0.03182057263 3
 
< 0.1%
6.571319854 × 10-203
 
< 0.1%
Other values (99971) 99992
99.9%
ValueCountFrequency (%)
2.681104154 × 10-201
< 0.1%
2.831186365 × 10-201
< 0.1%
2.840118182 × 10-201
< 0.1%
2.852876755 × 10-201
< 0.1%
2.878903144 × 10-201
< 0.1%
2.953432943 × 10-201
< 0.1%
2.960301288 × 10-201
< 0.1%
2.965494723 × 10-201
< 0.1%
2.971759128 × 10-201
< 0.1%
2.971807717 × 10-201
< 0.1%
ValueCountFrequency (%)
1 2
< 0.1%
0.9994805488 1
< 0.1%
0.9979021986 1
< 0.1%
0.9910649949 1
< 0.1%
0.9858674503 1
< 0.1%
0.9825650928 1
< 0.1%
0.9810319363 1
< 0.1%
0.9785790579 1
< 0.1%
0.9751971167 1
< 0.1%
0.9687721569 1
< 0.1%

Topic_19
Real number (ℝ)

Distinct99963
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.11569067
Minimum2.6811042 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:45.612670image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2.6811042 × 10-20
5-th percentile5.8830876 × 10-20
Q10.00054659893
median0.066393
Q30.17376008
95-th percentile0.39903515
Maximum1
Range1
Interquartile range (IQR)0.17321348

Descriptive statistics

Standard deviation0.14425167
Coefficient of variation (CV)1.2468738
Kurtosis5.4833936
Mean0.11569067
Median Absolute Deviation (MAD)0.066393
Skewness2.025846
Sum11579.48
Variance0.020808545
MonotonicityNot monotonic
2025-01-22T16:06:45.925213image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.05 68
 
0.1%
1 21
 
< 0.1%
1.649460308 × 10-194
 
< 0.1%
4.708774073 × 10-204
 
< 0.1%
6.196289274 × 10-204
 
< 0.1%
4.177598406 × 10-203
 
< 0.1%
6.971312359 × 10-203
 
< 0.1%
5.437215329 × 10-203
 
< 0.1%
4.610600655 × 10-193
 
< 0.1%
6.571319854 × 10-203
 
< 0.1%
Other values (99953) 99974
99.9%
ValueCountFrequency (%)
2.681104154 × 10-201
< 0.1%
2.784495699 × 10-201
< 0.1%
2.831186365 × 10-201
< 0.1%
2.840118182 × 10-201
< 0.1%
2.840253967 × 10-201
< 0.1%
2.842027472 × 10-201
< 0.1%
2.878903144 × 10-201
< 0.1%
2.953432943 × 10-201
< 0.1%
2.960301288 × 10-201
< 0.1%
2.965494723 × 10-201
< 0.1%
ValueCountFrequency (%)
1 21
< 0.1%
0.9997451273 1
 
< 0.1%
0.9987593858 1
 
< 0.1%
0.9981084302 1
 
< 0.1%
0.9976459493 1
 
< 0.1%
0.9973303927 1
 
< 0.1%
0.9968707269 1
 
< 0.1%
0.9949080753 1
 
< 0.1%
0.9944969364 1
 
< 0.1%
0.9927231453 1
 
< 0.1%

Topic_20
Real number (ℝ)

Distinct99982
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.033426847
Minimum2.8311864 × 10-20
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size782.1 KiB
2025-01-22T16:06:46.190418image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2.8311864 × 10-20
5-th percentile5.63408 × 10-20
Q18.8659534 × 10-20
median1.7467601 × 10-19
Q30.013164584
95-th percentile0.2434784
Maximum1
Range1
Interquartile range (IQR)0.013164584

Descriptive statistics

Standard deviation0.09994596
Coefficient of variation (CV)2.9899907
Kurtosis21.410485
Mean0.033426847
Median Absolute Deviation (MAD)1.1689736 × 10-19
Skewness4.3486338
Sum3345.6931
Variance0.009989195
MonotonicityNot monotonic
2025-01-22T16:06:46.452302image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.05 68
 
0.1%
6.196289274 × 10-204
 
< 0.1%
1.649460308 × 10-194
 
< 0.1%
4.708774073 × 10-204
 
< 0.1%
4.177598406 × 10-203
 
< 0.1%
0.00203957014 3
 
< 0.1%
6.571319854 × 10-203
 
< 0.1%
6.096213638 × 10-203
 
< 0.1%
5.437215329 × 10-203
 
< 0.1%
6.971312359 × 10-203
 
< 0.1%
Other values (99972) 99992
99.9%
ValueCountFrequency (%)
2.831186365 × 10-201
< 0.1%
2.840118182 × 10-201
< 0.1%
2.840253967 × 10-201
< 0.1%
2.842027472 × 10-201
< 0.1%
2.960301288 × 10-201
< 0.1%
2.965494723 × 10-201
< 0.1%
2.971759128 × 10-201
< 0.1%
2.979744931 × 10-201
< 0.1%
2.985114267 × 10-201
< 0.1%
2.990896896 × 10-201
< 0.1%
ValueCountFrequency (%)
1 1
< 0.1%
0.9966241475 1
< 0.1%
0.988963288 1
< 0.1%
0.9803808351 1
< 0.1%
0.9775227446 1
< 0.1%
0.959304292 1
< 0.1%
0.9534095045 1
< 0.1%
0.9532606109 1
< 0.1%
0.9449375179 1
< 0.1%
0.9440408125 1
< 0.1%

Interactions

2025-01-22T16:06:06.811767image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:03.139045image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:08.377737image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:13.396877image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:18.522420image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:23.871687image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:29.252448image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:34.236896image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:39.390601image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:44.339228image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:49.257919image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:54.308828image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:59.096178image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:04.069782image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:09.056221image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:14.534044image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:20.079756image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:25.879426image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
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2025-01-22T16:05:36.423535image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:41.816909image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:46.654373image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
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2025-01-22T16:04:44.522294image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:49.439865image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
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2025-01-22T16:04:59.279701image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:04.261004image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:09.242893image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
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2025-01-22T16:05:31.529726image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:36.612839image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:42.006940image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:46.843102image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:51.853032image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:56.908278image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
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2025-01-22T16:04:34.601847image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
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2025-01-22T16:04:44.707470image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
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2025-01-22T16:04:54.677370image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
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2025-01-22T16:05:04.446787image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:09.425655image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:14.983016image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:20.565600image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:26.446315image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:31.712338image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
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2025-01-22T16:05:25.277621image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:30.718084image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:35.832225image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:41.249795image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:46.073546image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:51.107495image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:55.901281image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:06:00.974246image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:06:06.145514image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:06:11.738491image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:08.009558image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:13.009930image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:18.134089image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:23.437092image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:28.872724image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:33.859968image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:39.022764image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:43.740861image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:48.894949image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:53.933898image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:58.730001image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:03.701865image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:08.683234image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:14.128122image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:19.626628image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:25.460242image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:30.967626image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:36.025110image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:41.431422image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:46.267029image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:51.294908image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:56.126167image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:06:01.169426image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:06:06.346156image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:06:11.944538image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:08.194166image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:13.208643image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:18.327064image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:23.671502image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:29.066935image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:34.054454image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:39.210856image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:44.138159image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:49.070435image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:54.125825image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:04:58.916396image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:03.886522image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:08.869046image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:14.315769image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:19.864295image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:25.650592image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:31.164370image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:36.229305image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:41.623278image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:46.460416image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:51.486327image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:05:56.317121image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:06:01.403217image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-22T16:06:06.546409image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Correlations

2025-01-22T16:06:46.701467image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Average_RatingHelpfulnessNum_of_RatingsRatingTopic_1Topic_10Topic_11Topic_12Topic_13Topic_14Topic_15Topic_16Topic_17Topic_18Topic_19Topic_2Topic_20Topic_3Topic_4Topic_5Topic_6Topic_7Topic_8Topic_9breadthdepth
Average_Rating1.000-0.1030.3320.1920.042-0.0940.0080.091-0.006-0.0660.159-0.066-0.009-0.027-0.103-0.1200.017-0.028-0.0000.0670.0510.0180.034-0.1370.071-0.038
Helpfulness-0.1031.000-0.0800.0110.0320.0230.012-0.0150.0130.062-0.0010.0330.0130.0220.0780.0190.0200.009-0.0120.0060.014-0.0090.0340.053-0.0850.073
Num_of_Ratings0.332-0.0801.0000.0860.046-0.033-0.0070.0100.004-0.072-0.048-0.010-0.034-0.099-0.051-0.0790.0190.0250.004-0.034-0.042-0.0190.020-0.0290.051-0.019
Rating0.1920.0110.0861.0000.0290.0410.0180.0410.0180.0600.0460.0310.0170.0150.1010.0350.0150.0260.0520.0270.0300.0320.0350.0680.0520.042
Topic_10.0420.0320.0460.0291.0000.0660.0300.0490.1080.0770.1020.0180.0320.0900.116-0.1970.1270.0270.0420.1530.0600.0550.0960.073-0.1520.189
Topic_10-0.0940.023-0.0330.0410.0661.0000.1510.0930.0870.1900.0980.1590.1480.1260.1160.0900.1900.1830.1270.0340.1030.1540.1120.327-0.2310.201
Topic_110.0080.012-0.0070.0180.0300.1511.0000.1830.2520.1170.0810.1090.1800.0720.116-0.0100.1860.1780.1320.1380.1810.2100.1920.172-0.2310.222
Topic_120.091-0.0150.0100.0410.0490.0930.1831.0000.2010.1300.2510.1260.2160.1550.0960.0570.1600.1700.1390.0990.2080.2290.2250.107-0.1630.160
Topic_13-0.0060.0130.0040.0180.1080.0870.2520.2011.0000.1100.1290.0690.1550.1160.1770.0040.1990.1100.1800.1180.1420.2000.1830.094-0.1760.182
Topic_14-0.0660.062-0.0720.0600.0770.1900.1170.1300.1101.0000.2290.1500.1070.2390.2430.0420.2250.1080.1230.1200.2240.0880.1250.259-0.3310.294
Topic_150.159-0.001-0.0480.0460.1020.0980.0810.2510.1290.2291.0000.0450.1670.3620.1280.0420.1670.0770.1000.2000.2650.1880.1300.069-0.2320.124
Topic_16-0.0660.033-0.0100.0310.0180.1590.1090.1260.0690.1500.0451.0000.1940.0920.0540.0740.1300.1230.0940.0510.1110.1080.0980.135-0.3410.301
Topic_17-0.0090.013-0.0340.0170.0320.1480.1800.2160.1550.1070.1670.1941.0000.1960.0890.0900.1550.1420.0900.1310.1540.2900.1930.126-0.1810.182
Topic_18-0.0270.022-0.0990.0150.0900.1260.0720.1550.1160.2390.3620.0920.1961.0000.1660.1030.1570.0890.1320.2360.2360.2140.1110.130-0.1840.147
Topic_19-0.1030.078-0.0510.1010.1160.1160.1160.0960.1770.2430.1280.0540.0890.1661.000-0.0170.1890.0700.0820.1180.1140.0800.1590.204-0.4420.212
Topic_2-0.1200.019-0.0790.035-0.1970.090-0.0100.0570.0040.0420.0420.0740.0900.103-0.0171.000-0.0110.0570.056-0.0580.0480.075-0.0420.088-0.3460.164
Topic_200.0170.0200.0190.0150.1270.1900.1860.1600.1990.2250.1670.1300.1550.1570.189-0.0111.0000.1500.1390.1560.2010.1330.2280.197-0.1880.188
Topic_3-0.0280.0090.0250.0260.0270.1830.1780.1700.1100.1080.0770.1230.1420.0890.0700.0570.1501.0000.0860.0430.0830.1570.1150.238-0.2080.201
Topic_4-0.000-0.0120.0040.0520.0420.1270.1320.1390.1800.1230.1000.0940.0900.1320.0820.0560.1390.0861.0000.0180.2160.1040.0420.098-0.1660.131
Topic_50.0670.006-0.0340.0270.1530.0340.1380.0990.1180.1200.2000.0510.1310.2360.118-0.0580.1560.0430.0181.0000.1330.1480.1930.054-0.2420.237
Topic_60.0510.014-0.0420.0300.0600.1030.1810.2080.1420.2240.2650.1110.1540.2360.1140.0480.2010.0830.2160.1331.0000.1570.1710.101-0.2250.208
Topic_70.018-0.009-0.0190.0320.0550.1540.2100.2290.2000.0880.1880.1080.2900.2140.0800.0750.1330.1570.1040.1480.1571.0000.1820.160-0.1380.139
Topic_80.0340.0340.0200.0350.0960.1120.1920.2250.1830.1250.1300.0980.1930.1110.159-0.0420.2280.1150.0420.1930.1710.1821.0000.125-0.2240.228
Topic_9-0.1370.053-0.0290.0680.0730.3270.1720.1070.0940.2590.0690.1350.1260.1300.2040.0880.1970.2380.0980.0540.1010.1600.1251.000-0.1980.193
breadth0.071-0.0850.0510.052-0.152-0.231-0.231-0.163-0.176-0.331-0.232-0.341-0.181-0.184-0.442-0.346-0.188-0.208-0.166-0.242-0.225-0.138-0.224-0.1981.000-0.898
depth-0.0380.073-0.0190.0420.1890.2010.2220.1600.1820.2940.1240.3010.1820.1470.2120.1640.1880.2010.1310.2370.2080.1390.2280.193-0.8981.000

Missing values

2025-01-22T16:06:12.726621image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
A simple visualization of nullity by column.
2025-01-22T16:06:13.841055image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Review_TextPosted_DateRatingAverage_RatingNum_of_RatingsHelpfulnessReviewerreview_titleLinkRating_DistributionRating_of_PerformanceRating_of_StorydepthbreadthTopic_1Topic_2Topic_3Topic_4Topic_5Topic_6Topic_7Topic_8Topic_9Topic_10Topic_11Topic_12Topic_13Topic_14Topic_15Topic_16Topic_17Topic_18Topic_19Topic_20
0I enjoyed both The Martian and Artemis so I preordered this one and started it immediately It did not disappoint Andy Weir is one of my favorite authors and Ray Porter is one of my favorite narrators so this combination is a winwin The narration is superb and the writing is great I recommend this book Dont over think it This is worth the price of admissionDisclaimer My enjoyment of the narrator is based on my listening speed I only leave 5 stars for books Ive listened to or will listen to multiple times05-04-2154.9182379656DavidgonzalezsrBazingahttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K162833,15895,2619,672,360156733,7989,1298,287,227145112,16872,2818,763,4160.9784171.2056732.573954e-026.102746e-208.783560e-026.102746e-202.587903e-031.954418e-038.605854e-021.513707e-016.102746e-207.883955e-021.172079e-019.101712e-041.133190e-015.749497e-046.102746e-201.475658e-011.268500e-016.102746e-200.0591866.102746e-20
1Awesome story telling Great build up of the characters and universe Cant compare to The Martian as that was novelunique, but this absolutely crushes Artemis Reminds me of a cross between Old Mans War and the Three Body Problem but slightly less cerebral than the latter05-05-2154.9182379159DavidAbsolutely Great way better than Artemishttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K162833,15895,2619,672,360156733,7989,1298,287,227145112,16872,2818,763,4160.8255231.3334235.050245e-032.794807e-013.168592e-017.236939e-022.363634e-043.262166e-022.929346e-043.837809e-031.359737e-196.106037e-032.528924e-033.733884e-026.177578e-032.755431e-021.225058e-021.565161e-014.456958e-031.387590e-020.0070441.540267e-02
2Let me start off by saying that I strongly enjoyed The Martian and Artemis please, please dont let the negative comments of others dissuade you from reading Artemis Until yesterday, American Gods was my unrivaled favorite as of finishing Project Hail Mary, it is now tied for my very favorite I will not provide spoilers, but if you enjoy good science fiction Scalzi, Taylor, Adams and understand that what makes good science fiction is good science, get Project Hail MaryAs for Ray Porter, I fell in love with his narration of We Are Legion We Are Bob and its sequels His enthusiastic, geeky, humorous, witty, and sarcastic tones are an absolute delight to my ears No other narrator could have done as well or betterI dont regret preordering both the audiobook and a signed copy of Project Hail Mary in the slightest To the contrary, I am elated and am looking forward to listening to this audiobook many, many times05-05-2154.9182379157RoswatheistHighest Order of Geekgasm Medalhttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K162833,15895,2619,672,360156733,7989,1298,287,227145112,16872,2818,763,4160.9581581.3576661.136803e-027.694041e-204.151269e-037.694041e-206.304988e-031.146112e-017.773207e-033.996658e-022.745889e-017.794174e-027.751753e-031.241193e-031.172261e-011.080583e-023.711716e-038.565076e-021.128719e-012.513728e-040.1077281.605514e-02
3Every once in a while Ill finish a book and cant help but get a bit depressed Knowing that the magic and intrigue you felt can never quite be captured again Part of this comes from completing it so quickly, I just couldnt put it down The other was I KNEW I would love it just because it was written by Andy Weir Most books it takes a few chapters to start getting into it but was hooked from the startWithout giving anything away Id say that its a mix of the Bobiverse and the Martian The amazing adventure that comes with space while geeking out on science projects05-11-2154.918237934J. KenneySo good, its depressinghttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K162833,15895,2619,672,360156733,7989,1298,287,227145112,16872,2818,763,4160.7954311.5426813.743268e-023.754833e-033.141182e-039.361982e-209.361982e-201.549407e-019.361982e-204.664184e-028.773143e-038.960701e-046.459749e-041.932430e-012.174365e-035.675086e-029.361982e-209.361982e-205.710936e-031.645215e-010.3213739.361982e-20
4In the Martian his high school science lecture content was acceptable because of the suspense Here, which as far as I can tell is an attempt to recreate that, it totally fails After several hours of boring basic science and NOTHING at all happening, I had enough Its just dull, the attempt at suspense seems manufactured and theres no action I really liked Artemis, and wish hes written a sequel to that I am returning this one disappointed05-08-2144.918237920CeliaNOT the Martianhttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K162833,15895,2619,672,360156733,7989,1298,287,227145112,16872,2818,763,4160.7698681.5709877.717619e-032.254546e-029.336233e-035.807929e-031.584921e-021.473462e-191.788971e-031.902603e-022.353674e-022.111607e-011.473462e-191.473462e-199.834022e-043.487543e-021.473462e-191.473462e-194.013335e-032.878688e-010.3105254.496473e-02
5I rarely write reviews but had to this time This was the best and most fun Ive had listening to an audiobook ever Perfect mix of science fiction and humor and just overall amazing The narrator is so talented Highly highly highly recommend06-25-2154.918237915EllenWow AMAZE AMAZE AMAZEhttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K162833,15895,2619,672,360156733,7989,1298,287,227145112,16872,2818,763,4160.7468342.0558025.026416e-205.026416e-202.258444e-045.026416e-205.026416e-205.026416e-203.958150e-011.143664e-015.076627e-035.026416e-208.421705e-031.393462e-011.095883e-015.026416e-205.026416e-208.859688e-027.920385e-035.026416e-200.1306435.026416e-20
6It has all the science we love from an Andy Weir book It makes you think and even look up stuff you didnt know, but it was a tad predictable If you love his other two books you will enjoy this readlisten Would have like to hear RC Bray as the narrator, the Martian audio book will always be one of my favorites While the narrator wasnt bad in this one, just wasnt sucked into the characters as much as with the Martian or even Artemis Maybe having preorder the book built up a hype He couldnt have possible matched but I did finish the book in three days I would recommend05-12-2144.91823797Robert SchenkSmart but predictablehttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K162833,15895,2619,672,360156733,7989,1298,287,227145112,16872,2818,763,4160.8029091.4952859.736080e-026.865760e-205.558899e-046.865760e-206.865760e-202.167992e-018.813624e-023.887367e-028.226455e-036.865760e-206.865760e-206.865760e-206.865760e-201.129631e-016.865760e-202.497520e-016.865760e-206.865760e-200.1873336.865760e-20
7if you know Andy Weir, this book will fit your expectations while still offering great surprises however, it also shows done of his weakness characters are generally flat, and the protagonists shallow sarcasm wears on you The reader performs it admirably, but the work could have benefited from backing off a bit rather than leaning into the goofinessThe inherently mysterious nature of the work makes it hard to discuss the plot or characters in a review, but suffice it to say that the incredible amount of research and thought that went into the science is on display, and theres some creative thinking there that seems both wondrous and plausible All the moving parts cone together on the end, but not without reasonable yet unexpected consequencesI enjoyed it, but of you arent a fan of Weir, try The Martian first05-12-2144.91823796jellyA fun Weir novel, but a step backhttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K162833,15895,2619,672,360156733,7989,1298,287,227145112,16872,2818,763,4160.9479670.8305684.627874e-023.758201e-021.540901e-017.601597e-031.123755e-191.359841e-021.021994e-035.543474e-031.997899e-021.577877e-014.295377e-031.428858e-026.004073e-031.765424e-023.630552e-021.644083e-011.515972e-021.653405e-020.2738088.059112e-03
8OUTSTANDING, JUST ABSOLUTELY OUTSTANDINGThis book will stay in your memories, The main characters will stay in your memories, and you will miss them10-10-2154.91823794Daniel C.TO JOE BISHOP SKIPPY ANDY SAYS,HOLD MY BEERhttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K162833,15895,2619,672,360156733,7989,1298,287,227145112,16872,2818,763,4160.7512271.3427941.130966e-012.321369e-022.301861e-199.167758e-022.301861e-193.685255e-022.301861e-192.301861e-192.301861e-192.301861e-192.301861e-195.700428e-022.301861e-195.338214e-032.301861e-192.581786e-011.534161e-022.149759e-020.3777992.301861e-19
9Definately Weir returning to his origins A single engineerscientist against all odds solving problems and making things workIts a good book Though the lack of interest in using the astrophage problem to solve it did become a bit annoying They have a 5000,000 ISP rocket engine and thats never used to deploy anti astrophage methods makes no senseThis does suffer from the Portal 2 dillema Is it as good as the Martian No Is it good Yes Below the Martian and Artemis, but still very readableI recommend reading Its a bit too long though05-11-2144.91823793PeterGood book, similar to the Martian, but not quitehttps://www.audible.com/pd/Project-Hail-Mary-Audiobook/B08G9PRS1K162833,15895,2619,672,360156733,7989,1298,287,227145112,16872,2818,763,4160.6546472.3665724.100858e-029.737103e-209.200635e-049.737103e-209.737103e-209.737103e-201.459511e-016.526192e-034.881668e-019.737103e-209.737103e-209.737103e-209.737103e-201.081188e-021.209132e-021.525594e-019.737103e-209.737103e-200.1304861.147815e-02
Review_TextPosted_DateRatingAverage_RatingNum_of_RatingsHelpfulnessReviewerreview_titleLinkRating_DistributionRating_of_PerformanceRating_of_StorydepthbreadthTopic_1Topic_2Topic_3Topic_4Topic_5Topic_6Topic_7Topic_8Topic_9Topic_10Topic_11Topic_12Topic_13Topic_14Topic_15Topic_16Topic_17Topic_18Topic_19Topic_20
100080Its a great story with a comedy twist, if you like ironic humor this novel will be a great read09-11-1854.6551450Kennethgreat novelhttps://www.audible.com/pd/The-Hitchhikers-Guide-to-the-Galaxy-Audiobook/B002VA9SWS40868,9576,3215,929,55740758,5054,1135,232,19234621,7996,3097,994,5940.5882072.3021645.735080e-201.488188e-014.352689e-015.735080e-201.722203e-016.442707e-065.735080e-205.735080e-205.735080e-205.735080e-205.735080e-205.735080e-205.735080e-202.297173e-015.735080e-205.735080e-201.005893e-023.909339e-035.735080e-205.735080e-20
100081Often found myself relistening to parts just because they were so funny I will be moving to the next book in the series and hope the humor keeps up07-05-1854.6551450Kainin MinceyLoved ithttps://www.audible.com/pd/The-Hitchhikers-Guide-to-the-Galaxy-Audiobook/B002VA9SWS40868,9576,3215,929,55740758,5054,1135,232,19234621,7996,3097,994,5940.7831251.1841811.413173e-012.459571e-022.236060e-022.734702e-021.772829e-198.063465e-021.640112e-022.103369e-021.444529e-022.481298e-023.687171e-021.772829e-191.772829e-191.772829e-191.772829e-191.458585e-021.659511e-031.322985e-025.092321e-015.147266e-02
100082Ive read Hitchhikers Guide before, wayyyyy back in high school Reading it again after so long away was amazing, and Stephen Frys narrator added a whole new facet to the book that I really loved Can we talk about how Douglas Adams description of Zaphods runterm as President of the Galaxy is all too prescient in the era of Trump Because I was getting chillsFunny Space SoBritish Tagsgiving Sweepstakes11-12-1854.6551450KaitlinStephen Fry Makes Ithttps://www.audible.com/pd/The-Hitchhikers-Guide-to-the-Galaxy-Audiobook/B002VA9SWS40868,9576,3215,929,55740758,5054,1135,232,19234621,7996,3097,994,5940.8624641.5133564.379875e-027.098905e-207.098905e-201.739991e-011.376050e-017.098905e-207.098905e-208.935813e-027.098905e-201.260307e-017.098905e-202.231282e-017.098905e-207.098905e-207.098905e-201.319028e-017.098905e-207.098905e-207.417731e-027.098905e-20
100083Great book and narrator It was a fun listen I wish all the books in the series were in one audiobook05-15-1854.6551450Aney1988Very enjoyablehttps://www.audible.com/pd/The-Hitchhikers-Guide-to-the-Galaxy-Audiobook/B002VA9SWS40868,9576,3215,929,55740758,5054,1135,232,19234621,7996,3097,994,5940.7312811.9372335.406658e-025.904734e-202.343882e-012.324219e-032.550606e-031.535271e-021.122375e-031.187075e-013.319979e-039.392268e-033.287617e-015.904734e-207.373288e-055.904734e-205.904734e-202.112606e-015.904734e-205.904734e-205.904734e-201.867961e-02
100084I mostly stick to NonFiction, but I decided to leave my comfort zone and check out this story The storytelling style is really fun, and the voiceover actor performs it in the perfect style The story itself is a crazy SciFi tale about this guy who goes all across the universe and is put in some wild situations Nonetheless the whole novel has some interesting food for thought that raises some neat philosophical ideas Id recommend Audible 20 Review Sweepstakes Entry11-14-1744.6551450KennethSciFi Comedy with some Philosophyhttps://www.audible.com/pd/The-Hitchhikers-Guide-to-the-Galaxy-Audiobook/B002VA9SWS40868,9576,3215,929,55740758,5054,1135,232,19234621,7996,3097,994,5940.9306291.0054307.226255e-032.764533e-017.213313e-032.889650e-047.634459e-031.072498e-021.881093e-012.128656e-021.825149e-021.701004e-014.503182e-022.206148e-031.159553e-192.281206e-021.387951e-032.636277e-026.432534e-021.743243e-021.084974e-014.655109e-03
100085This rendition is delicious If you have never read this book, listen to this audible book instead of reading it Its absolutely wonderful02-09-0954.6551450ElenaIts a classichttps://www.audible.com/pd/The-Hitchhikers-Guide-to-the-Galaxy-Audiobook/B002VA9SWS40868,9576,3215,929,55740758,5054,1135,232,19234621,7996,3097,994,5940.8109471.7036741.546452e-011.397143e-027.508903e-204.713165e-022.344023e-011.309409e-028.235706e-032.782942e-027.508903e-207.508903e-203.575196e-013.683328e-022.178741e-027.508903e-207.508903e-204.949138e-023.505857e-027.508903e-207.508903e-207.508903e-20
100086Stephen Fry is a master Enjoyed hearing him bring this amazing book to life Wonderful05-12-1854.6551450ColleenLove this bookhttps://www.audible.com/pd/The-Hitchhikers-Guide-to-the-Galaxy-Audiobook/B002VA9SWS40868,9576,3215,929,55740758,5054,1135,232,19234621,7996,3097,994,5940.7030922.0981125.506256e-024.597191e-038.026964e-201.720946e-041.146081e-028.026964e-202.178511e-038.026964e-208.026964e-202.160133e-011.591531e-023.568293e-018.026964e-208.026964e-202.591778e-014.361846e-023.497465e-028.026964e-208.026964e-208.026964e-20
100087narrator was absolutely perfect for such a good story everything I expected and more thank you04-27-1854.6551450Brandon ToppinsSci fi so goodhttps://www.audible.com/pd/The-Hitchhikers-Guide-to-the-Galaxy-Audiobook/B002VA9SWS40868,9576,3215,929,55740758,5054,1135,232,19234621,7996,3097,994,5940.7652531.7317897.142922e-202.012466e-017.142922e-205.414355e-027.142922e-201.962480e-027.142922e-201.334601e-033.058402e-017.142922e-207.142922e-203.779894e-021.077898e-027.142922e-206.302633e-022.633545e-014.285141e-027.142922e-207.142922e-207.142922e-20
100088This is the kind of book that allows your imagination to fully participate in the magic of the book while the jokescommentarysatire keep you laughing and awake for long stretches of road Kept us occupied on an allnight drive from Mexico to Colorado10-02-1054.6551450BillPerfect book for a road triphttps://www.audible.com/pd/The-Hitchhikers-Guide-to-the-Galaxy-Audiobook/B002VA9SWS40868,9576,3215,929,55740758,5054,1135,232,19234621,7996,3097,994,5940.6839841.7225824.250314e-013.212449e-022.157692e-022.122964e-023.391371e-191.617718e-023.391371e-194.275721e-021.474032e-027.591696e-032.652164e-023.391371e-194.829953e-024.935138e-033.391371e-193.391371e-193.391371e-193.391371e-193.390148e-013.391371e-19
100089Its been great revisiting this book Ive read it a few times already, but this was my first delve into the audiobook version Stephen Fry did a great job reading and placing the correct timing for the very British humour of the book10-25-1854.6551450James EdgeStill Holds Uphttps://www.audible.com/pd/The-Hitchhikers-Guide-to-the-Galaxy-Audiobook/B002VA9SWS40868,9576,3215,929,55740758,5054,1135,232,19234621,7996,3097,994,5940.7385561.9095378.938993e-025.908620e-203.451222e-015.908620e-201.452569e-015.908620e-207.195068e-031.175076e-015.908620e-205.908620e-201.075203e-024.634415e-038.945076e-035.908620e-205.908620e-202.474540e-015.908620e-205.908620e-205.908620e-202.374280e-02